205 Search Results

Neutron-Transformer Reflectometry Advanced Computation Engine (N-TRACE), a neural network model using a transformer architecture, is introduced for neutron reflectometry data analysis. It offers fast, accurate initial parameter estimations and efficient refinements, improving efficiency and precision for real-time data analysis of lithium-mediated nitrogen reduction for electrochemical ammonia synthesis, with relevance to other chemical transformations and batteries. Despite limitations in generalizing across systems, it shows promises for the use of transformers as the basis for models that could accelerate traditional approaches to modeling reflectometry data.

The reaction microenvironment plays a key role in dictating the selectivity of electrochemical CO₂ reduction. However, understanding the chemical nature of this microenvironment under operating conditions remains a substantial challenge. For this study, we employed attenuated total reflectance surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS) in operando for simultaneous measurements of reaction kinetics and concentrations of reactants and intermediates at the reaction interface, all under controlled mass transport conditions. These operando measurements enable direct correlations between the reaction microenvironment, mass transport, and kinetics for a Cu electrocatalyst, such as higher local concentrations of CO₂ under faster mass transport corresponding to higher rates of CO₂ reduction. We observed that faster mass transport decreased the *CO coverage at less negative potentials (-0.6 V_RHE) and increased the *CO coverage at more negative potentials (-1.1 V_RHE). We developed a transport-coupled kinetic model that captures these spectroscopic observations and provides insight into the processes controlling interfacial concentrations of reactants and intermediates, aiding future efforts toward tailoring reaction microenvironments.

The outdoor operation of electrochemical solar fuels devices must contend with challenges presented by the cycles of solar irradiance, temperature, and other meteorological factors. Herein, we discuss challenges associated with these fluctuations presented over three timescales, including the effects of diurnal cycling over the course of many days, a single diurnal cycle over the course of hours, and meteorological phenomena that cause fluctuations on the order of seconds to minutes. We also highlight both reaction-independent and reaction-specific effects of variable conditions for the hydrogen evolution reaction and CO₂ reduction reaction. We identify key areas of research for advancing the outdoor operation of solar fuels technology and highlight the need for metrics and benchmarks to enable the comparison of diurnal studies across systems and geographical locations.

Anion exchange membrane water electrolysis (AEMWE) is a promising technology to produce hydrogen from low-cost, renewable power sources. Recently, the efficiency and durability of AEMWE have improved significantly due to advances in the anion exchange polymers and catalysts. To achieve performances and lifetimes competitive with proton exchange membrane or liquid alkaline electrolyzers, however, improvements in the integration of materials into the membrane electrode assembly (MEA) are needed. In particular, the integration of the oxygen evolution reaction (OER) catalyst, ionomer, and transport layer in the anode catalyst layer has significant impacts on catalyst utilization and voltage losses due to the transport of gases, hydroxide ions, and electrons within the anode. This study investigates the effects of the properties of the OER catalyst and the catalyst layer morphology on performance. Using cross-sectional electron microscopy and in-plane conductivity measurements for four PGM-free catalysts, we determine the catalyst layer thickness, uniformity, and electronic conductivity and further use a transmission line model to relate these properties to the catalyst layer resistance and utilization. We find that increased loading is beneficial for catalysts with high electronic conductivity and uniform catalyst layers, resulting in up to 55% increase in current density at 2 V due to decreased kinetic and catalyst layer resistance losses, while for catalysts with lower conductivity and/or less uniform catalyst layers, there is minimal impact. This work provides important insights into the role of catalyst layer properties beyond intrinsic catalyst activity in AEMWE performance.

The reconstruction of Cu catalysts during electrochemical reduction of CO₂ is a widely known but poorly understood phenomenon. Herein, we examine the structural evolution of Cu nanocubes under CO₂ reduction reaction and its relevant reaction conditions using identical location transmission electron microscopy, cyclic voltammetry, in situ X-ray absorption fine structure spectroscopy and ab initio molecular dynamics simulation. Our results suggest that Cu catalysts reconstruct via a hitherto unexplored yet critical pathway - alkali cation-induced cathodic corrosion, when the electrode potential is more negative than an onset value (e.g., –0.4 V_RHE when using 0.1 M KHCO₃). Having alkali cations in the electrolyte is critical for such a process. Consequently, Cu catalysts will inevitably undergo surface reconstructions during a typical process of CO₂ reduction reaction, resulting in dynamic catalyst morphologies. While having these reconstructions does not necessarily preclude stable electrocatalytic reactions, they will indeed prohibit long-term selectivity and activity enhancement by controlling the morphology of Cu pre-catalysts. Alternatively, by operating Cu catalysts at less negative potentials in the CO electrochemical reduction, we show that Cu nanocubes can provide a much more stable selectivity advantage over spherical Cu nanoparticles.

Here, we developed a tandem, unassisted, solar-driven electrochemical and photothermocatalytic process for the single-pass conversion of CO₂ to butene using only simulated solar irradiation as the energetic input. The two-step process involves electrochemical CO₂ reduction (CO₂R) to ethylene followed by ethylene dimerization to butene. We assessed two unassisted electrochemical setups to concentrate ethylene in the CO₂R reactor, achieving concentrations up to 5.4 vol.% with 1.8% average solar-to-ethylene conversion and 5.6% average CO₂-to-ethylene single-pass conversion under 1-sun illumination. When passed through the photothermocatalytic ethylene oligomerization reactor, we generated 600 ppm of butene under 3-sun illumination. Through analysis of this process, we identified that the presence of H₂, CO, and H₂O leads to rapid deactivation of the Ni-based ethylene oligomerization catalyst.

Sluggish water oxidation reactions limit water electrolysis for H₂ production, which can be alleviated by the use of carbon-based ma- terials like agricultural wastes as reducing agents. Biochar from such biomass can reduce equilibrium cell potentials at standard condi- tions from 1.23 V to 0.21 V by avoiding direct water splitting at the anode. However, some challenges hinder biochar oxidation, including poor biochar binding, electrode caking, and surface passivation. We find that enhanced C/O ratio, crystallinity, and negative zeta potential improve biochar oxidation kinetics at mod- erate temperatures. Smaller particle sizes and better mixing pre- vent electrode caking, enhancing biochar stability. Here, we report sub-volt biochar-coupled H₂ production, often referred to as a bio- char-assisted water electrolysis (BAWE), yielding 250 mA/g_cat H₂ current at 100% Faradaic efficiency. Over 1 mA current was observed at a near-equilibrium cell potential of 0.2 V cell potential. Using a single-junction solar cell-powered BAWE, 15 mA H₂ is generated at 1 Sun, resulting in 4.8% solar-to-hydrogen efficiency, equivalent to 35% when the energy of H₂ relative to H₂O (without biochar) is assumed.

The lithium-mediated nitrogen reduction reaction (Li-NRR) represents a promising approach for electrochemical nitrogen activation, in which the solid electrolyte interphase (SEI) layer formed on the electrochemically plated lithium plays a key role. Herein, we used time-resolved, operando, grazing incidence wide-angle X-ray scattering (GI WAXS) to identify SEI species and reaction intermediates in the Li-NRR, comparing LiBF₄ and LiClO₄ as electrolyte salts. In this study, we demonstrated how the SEI composition influences the Li-NRR performance by regulating proton transport to the plated Li. When LiBF₄ is used as the electrolyte salt, the formation of LiF and lithium ethoxide (LiEtO) is observed. Reaction intermediates such as LiH and LiN_xH_y species were found and provide insight into reaction pathways towards undesired and desired products, respectively. Observed restructuring of the Cu (111) single crystal substrate also indicates interaction with plated Li that could possibly influence the Li-NRR performance. Together, these experiments give molecular insight into how to design Li-NRR systems and their SEI layers for optimal performance.

Metal-organic frameworks (MOFs) offer an interesting opportunity for catalysis, particularly for metal-nitrogen-carbon (M-N-C) motifs by providing an organized porous structural pattern and well-defined active sites for the oxygen reduction reaction (ORR), a key need for hydrogen fuel cells and related sustainable energy technologies. Here, in this work, we leverage electrochemical testing with computational models to study the electronic and structural properties in these systems and their relationship to ORR activity and stability based on dual transitional metal centers. These consists of two M1 metals with amine nodes coordinated to a single M2 metal with a phthalocyanine linker, where M1/M2 = Co, Ni, or Cu. Co-based metal centers, in particular Ni-Co, demonstrate the highest overall activity of all nine tested MOFs. Computationally, we identify the dominance of Co-sites, relative higher importance of the M2 site, and the role of layer M1 interactions on the ORR activity. Selectivity measurements indicate that M1 sites of MOFs, particularly Co, exhibits lowest (< 4%), and Ni demonstrates highest (>46%) two-electron selectivity, in good agreement with computational studies. Direct in-situ stability characterization, measuring dissolved metal ions, and calculations, using an alkaline stability metric, confirm that Co is the most stable metal in the MOF, while Cu exhibits notable instability at the M1. Overall, this study reveals how atomistic coupling of electronic and structural properties affects the ORR performance of dual site MOF catalysts and opens new avenues for tunable design and future development of these systems for practical electrochemical applications.

Multiphysics modeling enables probing of conditions inside a CO₂ electrolyzer that are difficult to measure, such as local concentrations and pH, as well as rapid testing of possible design changes. A one-dimensional model for a zero-gap membrane electrode assembly (MEA) CO₂ electrolyzer was developed with the assumption that catalyst layers interact with the membrane ionomer such that the ionomer affects the underlying kinetics. The kinetics for bicarbonate reacting to form hydrogen are fit using a planar electrode model for silver with an ionomer coating. The MEA model results are validated against experimental studies for current density and product selectivity. Flooding of the cathode is modeled using saturation curves, and results show that blocked pores in the microporous layer play a significant role in limiting the mass transport at high potentials (>2.8 V). Sensitivity studies showed that CO Faradaic efficiency can be increased by decreasing catalyst layer thickness and porosity, and decreasing KHCO₃ concentration.